Onsite Lead ML Engineer: Agentic AI & MLOps Lead

SPECTRAFORCE; Newark (NJ); On-site; USD 69,000 - 73,000; Full time

Job summary

SPECTRAFORCE in Newark, NJ is seeking a Lead Machine Learning Engineer to architect, develop, deploy, and scale ML and Agentic AI solutions addressing complex business challenges. You will collaborate with Product, Data Science, and Engineering teams to deliver production-grade AI systems.

Responsibilities include designing and deploying ML models, building scalable data pipelines in the cloud, advancing MLOps, monitoring performance and governance, and mentoring engineers.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Excellent problem-solving, communication, and collaboration skills.
• Experience in Agile development environments.
• Strong experience with ML workflows and AI lifecycle management.

Responsibilities

• Design, develop, and deploy ML models and Agentic AI solutions.
• Build scalable cloud-based ML applications and data pipelines.
• Develop and optimize MLOps processes, CI/CD pipelines, and model deployment frameworks.
• Monitor model performance, governance, observability, and reliability.
• Mentor engineering team members and lead technical problem-solving.

Skills

Traditional ML

Agentic AI

MLOps

Model Deployment

Cloud Engineering

Software Engineering

System Design

Python

C++

SQL

REST APIs

CI/CD

Data Engineering

Distributed Systems

AI Lifecycle

Education

Bachelor's degree in Computer Science/Engineering

Tools

TensorFlow

PyTorch

Scikit-learn

Spark/PySpark

GitHub Actions

Jenkins

CloudBees

Job description

SPECTRAFORCE in Newark, NJ is seeking a Lead Machine Learning Engineer to architect, develop, deploy, and scale ML and Agentic AI solutions addressing complex business challenges. You will collaborate with Product, Data Science, and Engineering teams to deliver production-grade AI systems.

Responsibilities include designing and deploying ML models, building scalable data pipelines in the cloud, advancing MLOps, monitoring performance and governance, and mentoring engineers.